Learn · Distinction

AI governance vs runtime governance

AI governance is the discipline of deciding what an organization's AI should be allowed to do and documenting it: policies, risk registers, model inventories, review boards. Runtime governance is the enforcement of those decisions in the path of each action, at the moment it executes, with verifiable evidence of the outcome.

The problem

Governance programmes produce artefacts that are accurate on the day they are written. Systems change faster than the artefacts do, and nothing in the artefact can stop an action.

Monitoring tools narrow the gap but sit beside the action rather than in front of it: they observe, they alert, and the action has already completed.

Why both are required

Runtime governance without a governance programme has nothing to enforce — someone still has to decide policy. A governance programme without runtime enforcement has no way to make the policy true.

How Skipr fits

Skipr is the enforcement half. Policies authored in the organization's governance process are evaluated per action, and the evidence produced feeds back into the same programme as proof rather than assertion.

Questions

Do I still need an AI governance platform?
If it is where your policy, risk and model inventory live, yes. Skipr enforces decisions; it does not replace the process that makes them.
Can monitoring substitute for runtime enforcement?
Monitoring tells you an action occurred. Enforcement determines whether it occurs. They answer different questions.
Which does a regulator ask about?
Increasingly both — the policy and the proof that it held while the system was running.

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